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Fractal Descriptors of Texture Images Based on the Triangular Prism Dimension

  • João Batista Florindo
  • Odemir Martinez Bruno
Article

Abstract

This work presents a novel descriptor for texture images based on fractal geometry and its application to image analysis. The descriptors are provided by estimating the triangular prism fractal dimension under different scales with a weight exponential parameter, followed by dimensionality reduction using Karhunen–Loève transform. The efficiency of the proposed descriptors is tested on four well-known texture data sets, that is, Brodatz, Vistex, UIUC and KTH-TIPS2b, both for classification and image retrieval. The novel method is also tested concerning invariances in situations when the textures are rotated or affected by Gaussian noise. The obtained results outperform other classical and state-of-the-art descriptors in the literature and demonstrate the power of the triangular descriptors in these tasks, suggesting their use in practical applications of image analysis based on texture features.

Keywords

Pattern recognition Texture analysis Fractal descriptors Triangular prism 

Notes

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Institute of Mathematics, Statistics and Scientific ComputingUniversity of CampinasCampinasBrazil
  2. 2.Scientific Computing Group, São Carlos Institute of PhysicsUniversity of São PauloSão CarlosBrazil

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